Synthetic aperture radar rapid imaging method and device based on neural network

Abstract

The invention discloses a synthetic aperture radar rapid imaging method based on a neural network, and the method comprises the steps: carrying out the low-resolution synthetic aperture radar imagingthrough employing a backward projection algorithm, carrying out the high-resolution reconstruction of an obtained low-resolution image through employing an image reconstruction model, and obtaining acorresponding high-resolution image, wherein the image reconstruction model is obtained through the following method by pre-training: performing low-resolution and high-resolution synthetic aperture radar imaging on a target by using the backward projection algorithm to obtain a training sample; and then training the neural network by taking low-resolution and high-resolution images in a series ofdifferent training samples as an input value and a true value respectively. The invention further discloses a synthetic aperture radar rapid imaging device based on the neural network. Compared witha traditional BP imaging algorithm, the method is small in calculation amount, high in operation rate, good in robustness and high in adaptive capacity.

Description

technical field [0001] The invention relates to the technical field of radar imaging, in particular to a synthetic aperture radar imaging method. Background technique [0002] Radar imaging technology is widely used in many fields of military and civilian use. With the increasing diversification of imaging scenarios and the continuous growth of application requirements, radar imaging technology also needs to be improved accordingly. [0003] Synthetic aperture radar (SAR) is a commonly used radar imaging method, which improves the imaging resolution by constructing an equivalent large observation aperture. In synthetic aperture imaging, frequency domain algorithms such as range Doppler (RD) and ω-k need to have an ideal uniform aperture, which has strict requirements on the motion state of the radar platform, although there are already some corresponding Advanced motion compensation algorithms have been continuously proposed, but they can only make the radar adapt to motio...

AI Technical Summary

Problems solved by technology

The disadvantage of these algorithms is that although a certain amount of BP algorithm calculation is reduced, they still do not meet the current real-time high-precision imaging requirements in terms of practicability, robustness, and imaging quality.

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